Introduction
In the digital commerce ecosystem, integrating user data from e-commerce platforms and shopping agent websites into spreadsheets for profile construction has emerged as a powerful strategy for precision marketing. This research explores methodologies for consolidating multi-source user data in spreadsheet environments to build comprehensive customer personas, subsequently applying these insights to enhance marketing conversion rates through data-driven strategies.
The spreadsheet-based approach offers unique advantages including accessibility, collaborative editing capabilities, and seamless integration with data analysis tools, making it ideal for small and medium enterprises seeking cost-effective marketing solutions.
Data Integration Framework
Data Collection Matrix
| Data Category | E-commerce Sources | Shopping Agent Sources |
|---|---|---|
| Demographics | Account registration data, Verified IDs | Shipping address information, Customs forms |
| Behavioral | Clickstream, Time-on-page, Wishlist | Search queries, Price comparison frequency |
| Transactional | Purchase history, Cart abandonment | Batch purchase patterns, Forwarding requests |
Data Normalization Techniques
- Temporal normalization
- Categorical mapping
- Currency conversion
- Geo-tagging
- Categorical mapping
Profile Construction Methodology
ML Algorithms Applied in Spreadsheets
- K-means clustering for customer segmentation =kmeans(data_range, 5)
- RFM scoring using quintile functions =percentile.inc
- Association rule mining via the Apriori algorithm implementation
- Predictive models using linear regression and decision trees
Profile Label Taxonomy
- Purchasing Power: Luxury afficcionadoBudget-conscious
- Engagement Level: Brand loyalistDeal hunter
- Cross-border Preference: US skincare specialistJP electronics expert
- Risk Profile: Early adopterReview dependent
Precision Marketing Implementation
Implementation Framework
- Dynamic pricing models
- Personalized email sequencing
- Geofenced promotions
- On-site recommendation engines
- Personalized email sequencing
Performance Metrics from Field Tests
| Strategy | CTR Improvement | Conversion Lift | ROAS Increase |
|---|---|---|---|
| Behavioral-triggered coupons | 37.2% | 28.5% | 140% |
| Localized inventory prompts | 52.1% | 41.8% | 210% |